## Loading required package: ggplot2
## Registered S3 methods overwritten by 'ggplot2':
## method from
## [.quosures rlang
## c.quosures rlang
## print.quosures rlang
## Loading required package: scales
## Loading required package: maptools
## Loading required package: sp
## Checking rgeos availability: TRUE
## Loading required package: maps
## Loading required package: grid
## Loading required package: Group4
## Loading required package: mapproj
## Loading required package: dplyr
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
## Loading required package: leaflet
En este Markdown se intenta representar el número de botnets activas. El dataset utilizado se actualiza cada 5 minutos.
La fuente de los datos utilizados es accesible desde el siguiente enlace https://feodotracker.abuse.ch/.
Mapa con la ubicación de las botnets.
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
## Registered S3 methods overwritten by 'ggplot2':
## method from
## [.quosures rlang
## c.quosures rlang
## print.quosures rlang
## Loading required package: car
## Loading required package: carData
##
## Attaching package: 'car'
## The following object is masked from 'package:dplyr':
##
## recode
## Loading required package: sandwich
## [1] "[*] Initial setup"
## [1] "[*] Read data from source"
## chr "data.frame"
## Type of dataset :
## Dimension(row x column) : 348 9
## Current lenght: 9 & Object size: 57008
## List of 9
## $ DetectedDate : chr [1:2] "POSIXct" "POSIXt"
## $ DstIP : chr "character"
## $ DstPort : chr "integer"
## $ LastOnlineDate : chr [1:2] "POSIXct" "POSIXt"
## $ Malware : chr "character"
## $ DetectedWeekday: chr "factor"
## $ continent_name : chr "character"
## $ country_code : chr "character"
## $ country_name : chr "character"
## Types of dataset fields: Printing
##
## print done
## Now let's see the values of all non-repeated fields
## 'data.frame': 348 obs. of 9 variables:
## $ DetectedDate : POSIXct, format: "2019-05-30 08:28:38" "2019-05-30 08:16:35" ...
## $ DstIP : chr "185.244.149.206" "94.23.174.183" "185.61.149.38" "176.223.133.178" ...
## $ DstPort : int 447 447 447 447 443 447 447 447 443 447 ...
## $ LastOnlineDate : POSIXct, format: "2019-06-01" "2019-06-02" ...
## $ Malware : chr "TrickBot" "TrickBot" "TrickBot" "TrickBot" ...
## $ DetectedWeekday: Factor w/ 7 levels "domingo","jueves",..: 2 2 2 2 2 2 5 5 5 5 ...
## $ continent_name : chr NA "Europe" "Europe" "Europe" ...
## $ country_code : chr NA "CZ" "LV" "RO" ...
## $ country_name : chr NA "Czech Republic" "Latvia" "Romania" ...
## Structure of the dataset fields:
## [1] "[*] Read RAW data from MaxMind"
## [1] "[*] Subseting scans data set"
## [1] "[*] Expanding MaxMind network ranges"
## [1] "[*] Foreach IP (source and destination) identify network range using parallel computing"
## [1] "[*] Joining source IP's with geolocation data"
## [1] "[*] Tidy data and save it"
echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.